In this study, it was aimed to investigate the impact of different missing data handling methods on DINA model parameter estimation and classification accuracy. In the study, simulated data were used and the data were generated by manipulating the number of items and sample size. In the generated data, two different missing data mechanisms…

Statistical education is a very important area of research because it builds knowledge and promotes innovation in the courses of this discipline. Based on the advances in this area, changes in the content and approaches of the courses at all educational levels have been promoted in several countries. In this study, we examine programs of…

The purpose of education should be to raise people who are researchers, developer, investigating what they find, use their knowledge in their behaviors and who can interpret and put new things on them. When children are being educated, the experience should be before the occurrence of the story. First, good and bad environment should be shown,…

In the age of "Big Data," information is often quantitative in nature. The ability to analyze information through the sifting of data has been identified as a core competency for success in navigating daily life and participation in the contemporary workforce. This skill, known as Quantitative Reasoning (QR), is characterized by the…

The Scholarship of Teaching and Learning (SoTL) has been described as the fastest growing academic development movement in higher education. As this field of inquiry matures, there is a need to understand how SoTL research is conducted. The purpose of our study was to inform this debate by investigating research approaches used in SoTL…

Sources of longitudinal achievement data are increasing thanks partially to the expansion of available interim assessments. These tests are often used to monitor the progress of students, classrooms, and schools within and across school years. Yet, few statistical models equipped to approximate the distinctly seasonal patterns in the data exist,…

Estimating the efficacy of different instructional modalities, techniques, and interventions is challenging because teaching style covaries with instructor, and the typical student only takes a course once. We introduce the individualized treatment effect (ITE) from analyses of personalized medicine as a means to quantify individual student…

Learning analytics (LA) has emerged as a field that offers promising new ways to prevent drop-out and aid retention. However, other research suggests that large datasets of learner activity can be used to understand online learning behaviour and improve pedagogy. While the use of LA in language learning has received little attention to date,…

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module…

Statistical investigations, a thread within the statistics strand of the mathematics and statistics learning area (Ministry of Education, 2007), are underpinned by the statistical enquiry cycle. As teachers introduce their students to the statistical enquiry cycle, they are supporting their students to become data detectives, posing and answering…

Purpose: Scientists in the speech, language, and hearing sciences rely on statistical analyses to help reveal complex relationships and patterns in the data collected from their research studies. However, data from studies in the fields of communication sciences and disorders rarely conform to the underlying assumptions of many traditional…

This paper describes a method for pooling grouped, ordered-categorical data across multiple waves to improve small-sample heteroskedastic ordered probit (HETOP) estimates of latent distributional parameters. We illustrate the method with aggregate proficiency data reporting the number of students in schools or districts scoring in each of a small…

The current study aimed to review studies on computational thinking (CT) indexed in Web of Science (WOS) and ERIC databases. A thorough search in electronic databases revealed 96 studies on computational thinking which were published between 2006 and 2016. Studies were exposed to a quantitative content analysis through using an article control…

As states consider non-academic measures of school quality for their accountability plans under the Every Student Succeeds Act, few are choosing to focus on the school climate in which students learn. That's not a surprise, given concerns about the validity and usefulness of existing climate surveys. However, the authors argue, a recent study…

In order to investigate causality in situations where random assignment is not possible, propensity scores can be used in regression adjustment, stratification, inverse-probability treatment weighting, or matching. The basic concepts behind propensity scores have been extensively described. When data are longitudinal or missing, the estimation and…